
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "143"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 80 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 76 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.942957	-0.804942	6.939932	0.637044	18.045944	-0.243320	4.922690	-0.183208	0.7744	0.8151	0.2314	16.964826	20.779441
2459593	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.384116	-1.304387	2.414614	0.292642	1.296567	-1.052948	1.303055	-0.820157	0.7546	0.7525	0.2425	6.100216	6.250424
2459592	RF_maintenance	100.00%	0.00%	0.00%	0.00%	-	-	3.391350	3.823505	35.505823	40.710281	36.411591	36.176986	1.399473	3.277036	0.7257	0.7394	0.4540	nan	nan
2459591	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.443183	-1.452657	3.241257	1.078599	1.094857	-0.172272	0.659234	-1.161565	0.6952	0.7096	0.3582	6.161888	5.499663
2459590	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	24.214498	-0.939962	3.397146	0.890498	14.187109	-0.000456	14.561600	-1.013763	0.6511	0.7065	0.3580	5.904062	6.942461
2459589	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	22.632159	-1.535264	3.043855	0.910775	20.608939	-0.597427	3.206988	-0.609200	0.6909	0.7332	0.2737	6.731168	8.574653
2459588	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.603973	-1.346953	3.406452	-0.009421	1.838916	-0.027658	1.288908	-0.681392	0.7990	0.7819	0.2124	11.680735	8.864819
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	1.900122	-1.135028	5.172261	1.582643	1.021359	-0.984550	0.265879	-1.281782	nan	nan	nan	6.768649	6.532960
2459586	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.260335	1.101342	3.186165	2.319158	8.261573	8.133135	6.490834	0.254153	0.6796	0.6951	0.3516	7.736295	7.305161
2459585	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	34.747772	36.516125	14.213798	15.683440	2.607764	4.608583	5.705510	5.839440	0.6681	0.6756	0.3675	0.000000	0.000000
2459584	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.225614	0.981087	3.680924	-0.212174	11.747004	-1.182558	2.472464	-0.965409	0.6306	0.6449	0.3559	0.842107	0.855591
2459583	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.313257	-0.400637	3.553534	-0.546289	4.141302	1.210790	-0.281823	-0.870689	0.6921	0.7090	0.3682	0.000000	0.000000
2459582	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.680618	-0.277284	2.930412	-0.408570	2.906432	0.552653	0.012249	-0.942575	0.6948	0.7101	0.3711	5.521468	5.298205
2459581	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.236166	-0.459809	3.527878	-0.083783	3.291481	0.304871	-0.223490	-1.032850	0.7015	0.7151	0.3649	6.009478	5.720361
2459580	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.872803	-0.406635	3.011624	0.029380	2.777338	0.795059	-0.543924	-1.137447	0.6958	0.7087	0.3671	0.000000	0.000000
2459579	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.934627	-0.548798	3.920832	-0.097547	3.033991	0.339539	-0.181642	-0.950120	0.6922	0.7055	0.3704	5.336742	5.268936
2459578	RF_maintenance	100.00%	0.00%	0.00%	0.00%	-	-	5.071288	4.584906	17.973347	22.764876	34.020245	37.368982	31.795017	26.717619	0.7462	0.7627	0.4603	nan	nan
2459577	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	37.875443	-0.677978	3.291092	-0.136148	16.460245	0.272841	4.364419	-0.979357	0.6285	0.7040	0.3794	5.138378	5.497143
2459576	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	35.307918	-0.801117	2.580805	-0.319926	7.235793	0.013176	1.664951	-0.858730	0.6380	0.7313	0.3753	5.526911	6.608301
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459574	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	15.993331	-0.635112	2.250397	-0.652867	13.510619	-0.751878	6.592320	-0.922479	0.6801	0.7269	0.3659	6.299580	6.812750
2459573	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.271990	-0.188425	4.442083	-0.080632	3.367141	0.197857	-0.227535	-0.510708	0.7116	0.7307	0.3631	7.602436	5.755355
2459572	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	44.221837	-0.478577	3.040009	-0.416886	4.732074	0.031244	1.374291	-0.676826	0.6035	0.7307	0.3713	4.172858	4.636836
2459571	RF_maintenance	100.00%	0.00%	0.00%	0.00%	-	-	2.564484	4.227704	19.657850	24.552848	107.428846	105.409860	58.415268	43.863494	0.6722	0.7273	0.4151	nan	nan
2459570	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	28.034420	-0.466379	2.735182	-0.287005	2.450627	0.337773	9.180103	0.440205	0.6285	0.7331	0.3463	0.000000	0.000000
2459569	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	17.691555	-0.478505	3.044386	-0.363523	9.674766	-0.589880	4.988412	-0.643580	0.7630	0.7971	0.2179	6.813505	5.548197
2459566	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.876350	-0.255048	3.470524	-0.253623	1.532474	0.071873	2.599645	0.274283	0.7036	0.7188	0.3858	6.436363	6.173317
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	0.042832	0.042832	0.026138	0.026138	-0.845420	-0.845420	-0.928844	-0.928844	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	8.993258	-0.774347	-0.213980	-1.724407	5.695941	0.239191	0.242135	1.111059	0.7081	0.7321	0.3761	6.593152	5.328986
2459563	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.862754	-0.377593	-0.466507	0.478994	0.206060	0.521858	-0.026180	-0.835427	0.7231	0.7315	0.3674	5.299235	4.794542
2459562	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.623129	-0.633287	1.831640	-0.646239	1.434120	0.559207	0.511448	-0.134377	0.7254	0.7375	0.3634	3.918075	3.541359
2459561	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.421076	-0.431299	1.808618	-0.651669	1.357320	0.920492	0.321688	-0.491728	0.7221	0.7374	0.3622	3.544602	3.264395
2459560	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.443763	-0.312470	1.967110	-0.718697	1.769085	1.067143	0.318815	-0.498323	0.7184	0.7308	0.3749	4.696335	3.946096
2459559	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.623464	-0.733893	1.809047	-0.943749	2.012394	0.978546	1.766275	-0.384774	0.7204	0.7305	0.3674	3.397892	3.074865
2459558	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.674617	0.114826	3.490355	-0.444812	2.568223	1.106553	1.142522	-0.680635	0.7250	0.7325	0.3700	4.376688	3.851820
2459557	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7936	0.7992	0.3507	nan	nan
2459556	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.062939	-0.423997	3.631675	-0.462484	2.764792	0.656272	-0.171563	-1.027442	0.7191	0.7301	0.3707	4.462126	3.787632
2459554	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7264	0.7360	0.3768	nan	nan
2459553	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7230	0.7316	0.3769	nan	nan
2459552	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.815561	-0.653917	4.716782	0.943385	5.227533	-2.108037	2.196998	-0.877324	0.7236	0.7344	0.3754	7.849907	8.946556
2459551	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.493092	-0.475024	2.095749	-1.003805	2.882259	1.097333	0.632779	0.012342	0.7242	0.7338	0.3731	3.858858	3.371095
2459550	RF_maintenance	-	27.18%	27.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.5328	0.5313	0.3212	nan	nan
2459549	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.273709	-0.275289	3.739580	-0.056377	3.147112	1.020182	3.983577	0.065671	0.7208	0.7319	0.3819	4.340774	3.849727
2459542	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	35.195443	-0.608826	5.107003	0.829687	1.868971	0.015605	4.991076	0.431030	0.7080	0.7763	0.3437	4.371393	4.015987
2459541	RF_maintenance	100.00%	1.34%	1.34%	0.00%	100.00%	0.00%	17.063398	-0.809806	4.141515	0.474553	8.678642	1.058132	5.182779	0.252959	0.7296	0.7670	0.3107	6.388043	5.370383
2459540	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.785000	-0.336372	1.985802	-0.630363	1.337023	-0.006573	0.641649	-0.382509	0.7702	0.7753	0.3197	4.080265	3.454139
2459536	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.811436	-1.122944	5.458402	1.704159	1.872456	-0.610833	0.139511	-1.333913	0.7542	0.7575	0.3884	9.187981	6.498964
2459535	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.323610	-0.593927	1.924065	-0.589991	1.957024	-0.488142	0.565916	-0.269773	0.8001	0.7982	0.3255	4.077859	3.378972
2459534	RF_maintenance	100.00%	98.66%	98.66%	0.00%	100.00%	0.00%	2.710338	3.259502	1.386978	-1.093453	2.398938	4.353561	8.838487	9.260068	0.0642	0.0906	0.0117	1.209381	1.213130
2459533	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.380807	-0.830392	3.713004	-0.054074	2.835969	1.154584	-0.296506	-0.794929	0.7436	0.7538	0.3766	5.278970	3.817239
2459532	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.220554	0.479970	5.017086	0.045958	3.191707	0.069956	-0.034837	-0.896026	0.7488	0.7579	0.3668	4.843188	3.812053
2459530	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.586926	-0.335419	1.673557	-0.685953	1.954286	0.531674	0.591652	-0.343001	0.7654	0.7669	0.3634	4.507200	4.089414
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.431181	-0.286959	5.009469	-0.370239	4.648230	0.120881	0.506012	-0.393953	0.9169	0.9467	0.2562	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	2.132250	-0.238131	5.547022	0.354626	1.039983	1.560114	0.627694	-0.288681	nan	nan	nan	6.371213	5.514488
2459522	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.769867	-0.753091	4.415489	0.400939	2.188688	-0.130891	1.721796	-0.234263	0.7287	0.7409	0.3008	5.831144	6.173428
2459513	RF_maintenance	100.00%	0.00%	0.00%	0.00%	-	-	5.247673	5.814053	18.504711	23.729322	27.810574	50.800959	20.013121	16.974219	0.8715	0.9220	0.2112	nan	nan
2459508	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.928128	-0.667348	4.573229	-1.049311	9.231245	-1.041754	8.386611	-1.207327	0.9257	0.9576	0.1382	0.000000	0.000000
2459505	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	1.732306	-0.486133	3.263601	0.148247	1.676237	0.498849	-0.653507	-0.927088	0.1108	0.1134	0.0065	1.225752	1.223353
2459503	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.865967	-0.432236	4.523720	0.727659	7.107973	0.274605	7.557502	-0.754645	0.8926	0.8915	0.3842	0.000000	0.000000
2459501	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	4.434207	-0.296461	3.854058	0.241704	2.915180	1.514659	2.559422	-0.888293	0.2082	0.2163	0.0446	0.000000	0.000000
2459500	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	3.476106	-0.918130	4.674041	-0.729988	6.134121	-0.717321	1.767742	-0.514457	0.2168	0.2317	0.0469	0.000000	0.000000
2459499	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	3.434031	-0.797301	5.836245	-0.713521	5.822970	-0.438134	0.656286	-0.675816	0.1921	0.2139	0.0220	0.000000	0.000000
2459498	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	2.715437	-0.658511	4.054621	0.063217	4.202159	-0.109938	0.158190	-0.790164	0.2020	0.2321	0.0476	0.000000	0.000000
2459497	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	3.616278	-0.031438	4.099021	0.473291	4.952454	1.217850	-0.191162	-0.837004	0.2537	0.2919	0.0578	0.000000	0.000000
2459496	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	4.026446	-1.043617	4.297603	0.127715	4.530873	0.795738	-0.407489	-0.827483	0.9262	0.9321	0.3526	0.000000	0.000000
2459495	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.183460	-0.514980	3.965264	0.118428	4.311863	0.687178	-0.266270	-0.881275	0.9230	0.9281	0.3795	0.000000	0.000000
2459494	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.274176	-0.630172	2.486127	-0.651663	5.337852	0.916492	49.330697	-0.793560	0.8982	0.9205	0.4145	0.000000	0.000000
2459492	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.101119	-0.219582	3.053851	1.356400	0.591878	2.904164	9.494875	-1.016700	0.7631	0.8133	0.3223	0.000000	0.000000
2459491	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	3.302179	-0.197759	2.996760	1.596336	10.546509	1.883242	4.484406	-1.073906	0.7965	0.8248	0.2668	0.000000	0.000000
2459490	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.954646	0.125112	2.581787	2.256693	1.017834	2.549103	5.370119	-0.579902	0.7545	0.8090	0.3644	0.000000	0.000000
2459489	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	15.068976	-0.311574	2.743757	1.427341	15.212337	3.414512	1.377272	-0.645585	0.7514	0.8159	0.3224	0.000000	0.000000
2459488	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	7.329489	-0.010710	-0.029788	1.250409	10.712158	2.595448	194.687825	-0.763772	0.7268	0.8195	0.3639	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 143 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 143, Node 14:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 143: 2459603

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Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶